Walkway Detection for Autonomous Light Electric Vehicle

Abstract

Systems and methods for detecting walkways using sensor data from an autonomous light electric vehicle are provided. A method can include obtaining, by a computing system comprising one or more computing devices, sensor data from a sensor located onboard an autonomous light electric vehicle. The method can further include determining, by the computing system, that the autonomous light electric vehicle is located on a walkway based at least in part on the sensor data. In response to determining that the autonomous light electric vehicle is located on the walkway, the method can further include determining, by the computing system, a control action to modify an operation or a location of the autonomous light electric vehicle. The method can further include implementing, by the computing system, the control action.

What is claimed is: 
     
         1 . A computer-implemented method for determining an autonomous light electric vehicle location, comprising:
 obtaining, by a computing system comprising one or more computing devices, sensor data from a sensor located onboard an autonomous light electric vehicle;   determining, by the computing system, that the autonomous light electric vehicle is located on a walkway based at least in part on the sensor data;   in response to determining that the autonomous light electric vehicle is located on the walkway, determining, by the computing system, a control action to modify an operation or a location of the autonomous light electric vehicle; and   implementing, by the computing system, the control action.   
     
     
         2 . The computer-implemented method of  claim 1 , further comprising:
 determining, by the computing system, a section of the walkway in which the autonomous light electric vehicle is located based at least in part on the sensor data;   wherein the section of the walkway comprises one of: a frontage zone, a pedestrian throughway, or a furniture zone.   
     
     
         3 . The computer-implemented method of  claim 2 , wherein determining, by the computing system, the control action to modify the operation or the location of the autonomous light electric vehicle comprises determining, by the computing system, the control action based at least in part on the section of the walkway in which the autonomous light electric vehicle is located. 
     
     
         4 . The computer-implemented method of  claim 1 , wherein the sensor data comprises accelerometer data, and wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises analyzing the accelerometer data for a walkway signature waveform. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein the sensor data comprises one or more images obtained from a camera located onboard the autonomous light electric vehicle, and wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises analyzing the one or more images using machine-learned model to determine the autonomous light electric vehicle is located on the walkway;
 wherein the machine-learned model comprises an image segmentation model which has been trained to detect a walkway or a walkway section using training data comprising a plurality of images labelled with walkway or walkway section annotations.   
     
     
         6 . The computer-implemented method of  claim 1 , wherein the sensor data comprises one or more images obtained from a camera located onboard the autonomous light electric vehicle, and wherein the one or more images comprise one or more images depicting one or more position identifiers of a plurality of position identifiers;
 wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises analyzing the one or more images using a machine-learned model to determine a location of the autonomous light electric vehicle; and   wherein the machine-learned model comprises a position identifier recognition model which has been trained to determine the location of the autonomous light electric vehicle based at least in part on the one or more position identifiers depicted in the one or more images.   
     
     
         7 . The computer-implemented method of  claim 1 , wherein the sensor data comprises one or more images obtained from a camera located onboard the autonomous light electric vehicle, and wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises analyzing the one or more images using a machine-learned model to determine a location of the autonomous light electric vehicle;
 wherein the machine-learned model comprises a visual localization model which has been trained to determine the location of the autonomous light electric vehicle by comparing the one or more images to an image map; and   wherein the image map comprises a map of a geographic area generated based at least in part on a plurality of images of the geographic area.   
     
     
         8 . The computer-implemented method of  claim 1 , wherein the computing system comprises a computing device located onboard the autonomous light electric vehicle; and
 wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises determining that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data by the computing device located onboard the autonomous light electric vehicle.   
     
     
         9 . The computer-implemented method of  claim 1 , wherein the computing system comprises a computing device remote from the autonomous light electric vehicle;
 wherein obtaining, by the computing system, the sensor data from the sensor located onboard the autonomous light electric vehicle comprises obtaining, by the remote computing device, the sensor data from the autonomous light electric vehicle; and   wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises determining, by the remote computing device, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data.   
     
     
         10 . The computer-implemented method of  claim 1 , further comprising:
 obtaining, from a computing device associated with a rider of the autonomous light electric vehicle, feedback associated with the rider operating the autonomous light electric vehicle on the walkway,   wherein determining, by the computing system, the control action to modify the operation or the location of the autonomous light electric vehicle action comprises determining, by the computing system, the control action based at least in part on the feedback, and   wherein the feedback comprises one or more of: feedback associated with a travelway obstruction; feedback associated with a weather condition; or feedback associated with a congestion level of the walkway.   
     
     
         11 . A computing system, comprising:
 one or more processors; and   one or more tangible, non-transitory, computer readable media that store instructions that when executed by the one or more processors cause the computing system to perform operations, the operations comprising:
 obtaining sensor data from a sensor located onboard an autonomous light electric vehicle; 
 determining that the autonomous light electric vehicle is located on a walkway based at least in part on the sensor data; 
 in response to determining that the autonomous light electric vehicle is located on the walkway, determining a control action to modify an operation or a location of the autonomous light electric vehicle; and 
 implementing the control action. 
   
     
     
         12 . The computing system of  claim 11 , wherein the sensor data comprises a signal received from one or more radio beacons, and wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises analyzing a strength of the signal received from the one or more radio beacons to determine a location of the autonomous light electric vehicle. 
     
     
         13 . The computing system of  claim 12 , wherein determining, by the computing system, that the autonomous light electric vehicle is located on the walkway based at least in part on the sensor data comprises inputting the sensor data from a plurality of sensors into a state estimator. 
     
     
         14 . The computing system of  claim 11 , wherein implementing, by the computing system, the control action comprises at least one of:
 sending a push notification to a computing device associated with a rider of the autonomous light electric vehicle; or   preventing a rider of the autonomous light electric vehicle from operating the autonomous light electric vehicle or another autonomous light electric vehicle at a future time.   
     
     
         15 . The computing system of  claim 11 , wherein implementing, by the computing system, the control action comprises autonomously moving the autonomous LEV to a different location. 
     
     
         16 . An autonomous light electric vehicle comprising:
 one or more sensors;   one or more processors; and   one or more tangible, non-transitory, computer readable media that store instructions that when executed by the one or more processors cause the computing system to perform operations, the operations comprising:
 obtaining sensor data from the one or more sensors; 
 determining that the autonomous light electric vehicle is located on a walkway based at least in part on the sensor data; 
 in response to determining that the autonomous light electric vehicle is located on the walkway, determining a control action to modify an operation or a location of the autonomous light electric vehicle; and 
 implementing the control action. 
   
     
     
         17 . The autonomous light electric vehicle of  claim 16 , wherein the autonomous light electric vehicle comprises a bicycle or a scooter. 
     
     
         18 . The autonomous light electric vehicle of  claim 16 , wherein the operations further comprise:
 determining a section of the walkway in which the autonomous light electric vehicle is located based at least in part on the sensor data.   
     
     
         19 . The autonomous light electric vehicle of  claim 18 , wherein determining the control action to modify the operation or the location of the autonomous light electric vehicle comprises determining the control action based at least in part on the section of the walkway in which the autonomous light electric vehicle is located. 
     
     
         20 . The autonomous light electric vehicle of  claim 16 , wherein the control action comprises autonomously moving the autonomous LEV to a different location.